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        "description": "\nThis is a frugal python package with some hyperspectral data goodies.\nThe whole source, including tests, can be found\n[on github](https://github.com/irap-omp/hyperspectral).\n\nHow to install\n==============\n\nThe setup script is build atop `distutils`, so you can read the\n[official documentation](https://docs.python.org/2/install/index.html#the-new-standard-distutils)\nfor installation instructions.\n\nTo summarize, you can install via `pip` or via the `setup` script :\n```\npip install hyperspectral\n```\nor\n```\npython setup.py install\n```\n\nHow to publish\n==============\n\nCopy `.pypirc` to `~/.pypirc`. Fill out the `password` field. (ask me !)\n\n```\npython setup.py sdist && twine upload dist/*\n```\n\nDependencies\n============\n\n- [astropy](http://www.astropy.org)\n- [numpy](http://www.numpy.org)\n\nIf you run `setup.py`, you'll need\n[distutils](https://docs.python.org/2/install/index.html) too.\n\nTesting Dependencies\n====================\n\nYou don't need those unless you're running the test suite.\n\n- [unittest](https://docs.python.org/2/library/unittest.html)\n- [ddt](https://github.com/txels/ddt)\n\n\nHyperspectral Cube\n==================\n\nA wrapper for 3D data with two spatial dimensions and one spectral dimension.\nIt extends `astropy.nddata.NDData` and makes a heavy usage of `astropy.units`.\nIt main purpose is to sanitize and uniformize hyperspectral cubes from FITS\nfiles that were made by careless astronomers, with header cards (FITS metadata)\nranging from exotic to blatantly illegal.\n",
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